Cloudera

NOVEMBER 13, 2020

Impala Optimizations for Small Queries. We’ll discuss the various phases Impala takes a query through and how small query optimizations are incorporated into the design of each phase. Query optimization in databases is a long standing area of research, with much emphasis on finding near optimal query plans.

Optimization 143

Optimization Metadata Statistics Cost-Benefit 143

Cloudera

FEBRUARY 8, 2024

Queries containing joins, filters, projections, group-by, or aggregations without group-by can be transparently rewritten by the Hive optimizer to use one or more eligible materialized views. The snapshotId of the source tables involved in the materialized view are also maintained in the metadata.

Snapshot 90

Snapshot Metadata Cost-Benefit Data Warehouse 90

AWS Big Data

JUNE 9, 2023

Despite these capabilities, data lakes are not databases, and object storage does not provide support for ACID processing semantics, which you may require to effectively optimize and manage your data at scale across hundreds or thousands of users using a multitude of different technologies.

Data Lake 115

Data Lake Metadata Optimization Statistics 115

Cloudera

JULY 13, 2023

A range of Iceberg table analysis such as listing table’s data file, selecting table snapshot, partition filtering, and predicate filtering can be delegated through Iceberg Java API instead, obviating the need for each query engine to implement it themself. The data files and metadata files in Iceberg format are immutable.

Metadata 70

Metadata Snapshot Data Warehouse Statistics 70

Smart Data Collective

AUGUST 25, 2020

Some of the benefits are detailed below: Optimizing metadata for greater reach and branding benefits. One of the most overlooked factors is metadata. Metadata is important for numerous reasons. Search engines crawl metadata of image files, videos and other visual creative when they are indexing websites.

Data mining 109

Data mining Metadata Big Data ROI 109

AWS Big Data

JULY 3, 2023

This helps traders determine the potential profitability of a strategy and identify any risks associated with it, enabling them to optimize it for better performance. With scalable metadata indexing, Apache Iceberg is able to deliver performant queries to a variety of engines such as Spark and Athena by reducing planning time.

Snapshot 86

Snapshot Data Lake Testing Strategy 86

AWS Big Data

SEPTEMBER 13, 2023

Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables. The File Manager Lambda function consumes those messages, parses the metadata, and inserts the metadata to the DynamoDB table odpf_file_tracker.

Data Lake 93

Data Lake Data Processing Metadata Snapshot 93